If the user supplies a data frame with all the same label (for instance, all female), and attempts to run AES-PCA on this with the single-level factor as a response, two things will happen:
the code will take 2-3 times longer to execute (no idea why), and
all the p-values will be 0 (is this bad?)
Normally, this would not happen, as predicting the outcome of a variable that's always TRUE doesn't seem like a reasonable thing to do, so we should add a warning.
If the user supplies a data frame with all the same label (for instance, all female), and attempts to run AES-PCA on this with the single-level factor as a response, two things will happen:
Normally, this would not happen, as predicting the outcome of a variable that's always
TRUEdoesn't seem like a reasonable thing to do, so we should add a warning.